Computer Vision

Description

Mind Map on Computer Vision, created by Jonathan Zinger on 05/07/2014.
Jonathan Zinger
Mind Map by Jonathan Zinger, updated more than 1 year ago
Jonathan Zinger
Created by Jonathan Zinger over 10 years ago
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Resource summary

Computer Vision
  1. Challenges
    1. Deformation
      1. Illumination
        1. Occlusion
          1. Scale
            1. Viewpoint
              1. Clutter
                1. Motion
                  1. Intra-Class Variation
                    1. Local Ambiguity
                    2. Cues
                      1. Depth
                        1. Linear Perspective
                          1. Aerial Perspective
                          2. Shape and lighting
                            1. Shading
                            2. Grouping
                              1. Common Fate
                            3. Connected to:
                              1. ML
                                1. AI
                                  1. Robotics
                                    1. Image Processing
                                    2. Vision
                                      1. I. Basic Processing - feature detection
                                        1. 2 Fitting & Grouping
                                          1. 3 Multi-view Geometry
                                            1. 4 Recognition
                                              1. 5 Semantic Segmentation
                                                1. Object Recognition
                                                  1. Problems
                                                    1. Post Est. Where is it in 3d?
                                                      1. Segmentation - Where is it in 2d
                                                        1. Recognition - What is it
                                                        2. Attempts
                                                          1. Recognition from appearance
                                                            1. Recognition from Geometry
                                                              1. Best: view based, local invariance,' lots of features and voting
                                                              2. Features
                                                                1. Distinctive
                                                                  1. many per object
                                                                    1. Easy to detect
                                                                  2. Object Categorization
                                                                    1. MAP - bayes
                                                                    2. Face Detection
                                                                      1. Slide window across image - evaluate face model
                                                                    3. Robotics
                                                                      1. Where am i
                                                                        1. SLAM
                                                                        2. Whats nearby
                                                                          1. Navigation/Learning
                                                                        3. Perception
                                                                          1. Computation STereo
                                                                            1. Feature Detection
                                                                              1. Motion Tracking
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